Performance of Node-RADS for Standardized Diagnosis of Cervical Lymph Nodes in Oral Squamous Cell Carcinoma

Objectives Current imaging techniques for diagnosing cervical lymph node metastasis (LNM) in oral squamous cell carcinoma (OSCC) lack consensus. The Node-RADS (Node Reporting and Data System) offers a criterion to evaluate LNM based on size and configuration. This study aimed to explore the correlation between Node-RADS scores and LNM rates in OSCC, and assess diagnostic performance. Materials and Methods A retrospective analysis was conducted on 200 patients (average age, 57.8 years, 73.5% were male) diagnosed with OSCC at the Peking University School of Stomatology, who underwent neck dissection, preoperative contrast enhanced CT scans, and had definitive postoperative pathological results. The correlation between Node-RADS scores and LNM rates was examined, various cutoff points (> 1,>2,>3,>4) was applied to evaluate sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV). The ROC and AUC were used to assess diagnostic efficacy. Additionally, the optimal short-axis diameter length and each configuration criterion were determined, while Kappa statistics evaluated inter-rater reliability. Results There was a notable linear correlation between Node-RADS scores and LNM rates. With increasing Node-RADS cutoff values, specificity and PPV increased from 5.6% to 97.2% and 65.3% to 97.5%, sensitivity and NPV decreased from 100% to 60.2% and 100% to 57.9%. The most effective Node-RADS cutoff values for individual patient, lymph node laterality and lymph node level dimension were respectively identified as > 3/>3/>2, with corresponding AUCs of 0.86/0.86/0.82. The Kappa consistency test yielded a value of 0.814. Conclusions This study establishes a groundwork for implementing the Node-RADS in assessing LNM in OSCC, also suggests it has moderate to high accuracy and robust diagnostic performance. Clinical Relevance: The results of this study suggest that Node Reporting and Data System is a reliable tool for guiding clinical decisions in the management of oral squamous cell carcinoma.